Quality specifications of routine clinical chemistry methods based on sigma metrics in performance evaluation

Xia, Jun; Chen, Su-feng; Xu, Fei; Zhou, Yongchao

doi:10.1002/jcla.22284

Cited by 19 publications

(19 citation statements)

References 17 publications

(15 reference statements)

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“…from Belgium and Xia J et al. from China [ 3 , 17 ]. Further for analytes showing poor performance in terms of σ < 3, the cause for poor performance was evaluated using QGI index similar to study performed by Verma M et al.…”

Section: Discussionmentioning

confidence: 99%

“…and Xia J et al. [ 3 , 17 ] Using biological variability data, σ metrics ranged from 0.8 to 8.02 for Level-2 and from 0.84 to 9.77 for Level-3. Performance analysis for 14 parameters revealed σ < 3 (poor performance) for 5 parameters of level 2 IQC (AST, Total protein, Glucose, BUN and ALT), 2 analytes of level 3 IQC (BUN, ALT) using TEa values as per CLIA guidelines while using Biological Variability data guidelines; poor performance (σ < 3) was seen for 10 parameters of level 2 IQC (AST, ALP, Alb, Total protein, Glucose, BUN, creatinine, ALT, Ca and HDL), 5 analytes of level 3 IQC (ALP, Alb, Total Protein, Glucose and HDL).…”

Section: Discussionmentioning

confidence: 99%

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Analysis of performance of clinical biochemistry laboratory using Sigma metrics and Quality Goal Index

Goel

Malik

Prasad

et al. 2021

Practical Laboratory Medicine

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Background Unreliable and ingenuine results issued by clinical laboratories have serious consequences for the patients. Sigma metrics is a standardized tool for Quality assessment for test performance in a laboratory. Objective To evaluate the performance of routine biochemistry laboratory at MMIMSR, Mullana in terms of Sigma metrics and Quality Goal Index. Material and methods This cross sectional study evaluated performance of 14 routine chemistry parameters using retrospective Internal Quality Control data of two levels on Siemens Dimension Rxl from Feb to Jul 2019 for CV% and EQAS reports from CMC, Vellore for Bias%. Sigma metrics was calculated using total allowable error targets as per CLIA and Biological Variability database guidelines. Results For level-2 IQC; TG, Chol, ALP showed excellent performance with σ > 6 while σ < 3 was observed for AST, Total Protein, Glucose, BUN and ALT using CLIA guidelines while in IQC Level-3 poor performers were only BUN and ALT with Ca, TG and Chol showing σ > 6. Further by using Biological Variability data guidelines; 10 parameters of IQC Level-2 and 5 of IQC level-3 were poor performers with σ < 3. Conclusion Sigma metrics is an excellent tool for performance analysis of tests performed in a clinical laboratory. Lack of precision in terms of CV% was seen for majority of the poor performers. Total allowable error targets using Biological Variability data revealed σ < 3 for 10 parameters while using CLIA guidelines σ < 3 was seen for only 5 parameters of IQC level-2.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Analysis of performance of clinical biochemistry laboratory using Sigma metrics and Quality Goal Index

Goel

Malik

Prasad

et al. 2021

Practical Laboratory Medicine

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“…These authors therefore suggested that no less than two concentrations of quality control products should be used every day for internal quality control to ensure acceptable test results . Xia et al also showed that sigma metric is a useful tool to evaluate assay performance and suggested that an assay with a high sigma value could use a simple internal quality control rule, whereas an assay with a low sigma value should be monitored strictly. The conclusions of our study are in agreement with the results of the above scholars, indicating that sigma metrics can play an important role in the field of quality control.…”

Section: Discussionmentioning

confidence: 99%

Application of Six Sigma for evaluating the analytical quality of tumor marker assays

Liu

Yang

et al. 2018

Clinical Laboratory Analysis

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Context The results of detection assays for the same specimen are usually quite different in different laboratories or when tested with different detection systems. Objective This study was designed to investigate the value of applying sigma metrics derived from different standards for allowable total error (TEa) in evaluating the analytical quality of tumor marker assays. Methods Assays were evaluated for these six tumor markers: total prostate‐specific antigen (tPSA), carcinoembryonic antigen (CEA), alpha‐fetoprotein (AFP), carbohydrate antigen 199 (CA199), carbohydrate antigen 125 (CA125), and carbohydrate antigen 153 (CA153). Sigma values were calculated for two concentrations of quality control products to assess differences in quality of tumor marker assays. Improvement measures were recommended according to the quality goal index, and appropriate quality control rules were selected according to the sigma value. Results The sigma value was highest using the higher biological variation‐derived “appropriate” TEa standard: it was sigma ≥6 or higher in 16.7% of tumor markers. Sigma was below 6 for all tumor markers using the other three TEa. CEA, AFP, CA199, CA125, and CA153 required improved precision. The marker tPSA required improve precision and accuracy. According to sigma values by using China's external quality assessment standards, CEA, AFP, CA125, and CA153 require 1 3s /2 2s /R 4s /4 1s multirules for internal quality control, CA199 requires use of 1 3s /2 2s /R 4s /4 1s /8 x multirules, and tPSA requires maximum quality control rules. Conclusion Six Sigma is useful for evaluating performance of tumor markers assays and has important application value in the quality control of these assays.

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“…2 Sigma metric has become a useful tool to monitor quality indicators, 1 to assess the analytical quality of assays, 3,4 to set quality control rules, [5][6][7][8] to describe assay analytical performance for external quality assessment participants, 9 and to help manufacturers choose product requirements. 8,11 Thus, laboratories have to take into account which TEa specification is most appropriate initially. The TEa from various sources, such as the Clinical Laboratory Improvement Amendments (CLIA), the College of American Pathologists (CAP), Reference Institute for Bioanalytics (Rilibak), the Royal College of Pathologists of Australasia (RCPA), and the China National Center for Clinical Laboratories (NCCL) external quality assessment goals, is associated with significantly different Sigma metrics for the same assay.…”

Section: Sigma (σ) Metric Was First Introduced Into Clinical Laboratomentioning

confidence: 99%

“…The TEa from various sources, such as the Clinical Laboratory Improvement Amendments (CLIA), the College of American Pathologists (CAP), Reference Institute for Bioanalytics (Rilibak), the Royal College of Pathologists of Australasia (RCPA), and the China National Center for Clinical Laboratories (NCCL) external quality assessment goals, is associated with significantly different Sigma metrics for the same assay. 8,11 Thus, laboratories have to take into account which TEa specification is most appropriate initially.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach

Wang

Gong

et al. 2019

Clinical Laboratory Analysis

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IntroductionTwo methods were compared for evaluating the sigma metrics of clinical biochemistry tests using two different allowable total error (TEa) specifications.Materials and methodsThe imprecision (CV%) and bias (bias%) of 19 clinical biochemistry analytes were calculated using a trueness verification proficiency testing (TPT)‐based approach and an internal quality control data inter‐laboratory comparison (IQC)‐based approach, respectively. Two sources of total allowable error (TEa), the Clinical Laboratory Improvement Amendments of 1988 (CLIA '88) and the People's Republic of China Health Industry Standard (WS/T 403‐2012), were used to calculate the sigma metrics (σCLIA, σWS/T). Sigma metrics were calculated to provide a single value for assessing the quality of each test based on a single concentration level.ResultsFor both approaches, σCLIA > σWS/T in 18 out of 19 assays. For the TPT‐based approach, 16 assays showed σCLIA > 3, and 12 assays showed σWS/T > 3. For the IQC‐based approach, 19 and 16 assays showed σCLIA > 3 and σWS/T > 3, respectively.ConclusionsBoth methods can be used as references for calculating sigma metrics and designing QC schedules in clinical laboratories. Sigma metrics should be evaluated comprehensively by different approaches.

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Quality specifications of routine clinical chemistry methods based on sigma metrics in performance evaluation

Abstract: Sigma metrics are an optimal tool to evaluate the performance of different assays. An assay with a high value could use a simple internal quality control rule, while an assay with a low value should be monitored strictly.

Cited by 19 publications

References 17 publications

Analysis of performance of clinical biochemistry laboratory using Sigma metrics and Quality Goal Index

Analysis of performance of clinical biochemistry laboratory using Sigma metrics and Quality Goal Index

Application of Six Sigma for evaluating the analytical quality of tumor marker assays

Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing‐based approach and an internal quality control data inter‐laboratory comparison‐based approach

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